Wiener–Khinchin theorem

In applied mathematics and statistics, the Wiener–Khinchin theorem or Wiener–Khintchine theorem, also known as the Wiener–Khinchin–Einstein theorem or the Khinchin–Kolmogorov theorem, states that the power spectral density of a wide-sense-stationary random process is equal to the Fourier transform of that process's autocorrelation function. == History == Norbert Wiener proved this theorem for the case of a deterministic function in 1930; Aleksandr Khinchin later formulated an analogous result for stationary stochastic processes and published that probabilistic analogue in 1934.

Source: Wikipedia — Wiener–Khinchin theorem (CC BY-SA 4.0)

Wiener–Khinchin theorem

In applied mathematics and statistics, the Wiener–Khinchin theorem or Wiener–Khintchine theorem, also known as the Wiener–Khinchin–Einstein theorem or the Khinchin–Kolmogorov theorem, states that the power spectral density of a wide-sense-stationary random process is equal to the Fourier transform of that process's autocorrelation function. == History == Norbert Wiener proved this theorem for the case of a deterministic function in 1930; Aleksandr Khinchin later formulated an analogous result for stationary stochastic processes and published that probabilistic analogue in 1934.

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Source: Wikipedia "Wiener–Khinchin theorem" · CC BY-SA 4.0

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